The dynamics of reading in non-Roman writing systems: a Reading and Writing Special Issue

Abstract

This paper provides a short overview of current issues in research on continuous reading in non-Roman orthographies. At the same time it also serves as an introduction to the present Reading and Writing Special Issue on this topic. The main questions examined in the contributions to this volume are closely related to issues that have been central to research debates on reading in English, German and French. However, we argue that these innovative approaches to the dynamics of reading in Chinese, Japanese and Korean go far beyond a simple comparative research strategy. Instead, by illuminating phenomena like word segmentation, parafoveal processing and semantic analysis from their unique perspectives, they provide valuable insights into the more general question of to what extent information processing in reading is universal as opposed to language specific. Moreover, we expect that these initial studies will trigger more basic research on non-alphabetic reading, providing a foundation for useful application.

Do Chinese Readers Follow the National Standard Rules for Word Segmentation during Reading?

“…Several researchers have suggested that understanding what information readers use to identify word boundaries is necessary for developing computational models of sentence reading in non-alphabetic languages [9], [36], [37]. However, most theoretical developments have been proposed based on alphabetic languages such as English, while relatively little work has been conducted on non-alphabetic languages such as Chinese.…”

Inserting spaces into Chinese text helps readers to learn new words: An eye movement study

“…Specifically, we investigated the impact of providing a clear visual cue to the location of word boundaries on the formation of novel lexical representations (as opposed to examining reading of words that already have lexical representations). As argued by Winskel et al (2009), understanding what information readers use to identify word boundaries is necessary for developing computational models of sentence reading that include non-alphabetic languages (see also Reilly & Radach, 2012). Most current theoretical models of Chinese word identification are limited to single words (except Li, Rayner, & Cave, 2009), and do not include any mechanism for text segmentationthese models are discussed in more detail in a later section of the ''Introduction".…”

The role of character positional frequency on Chinese word learning during natural reading

“…To address this question, we examined learning of pseudowords embedded in sentences, allowing us to determine which of our manipulated segmentation cues impacted upon readers’ ability to identify and group together the constituent characters. The exploration of this question will inform and encourage developments in computational models of sentence and text-level reading that include non-alphabetic languages [ 32 ]. There are a number of computational models that can account for many of the behavioral phenomena associated with reading; however, most of those models have been developed to account for reading of alphabetic writing systems, such as E-Z Reader model[ 33 ], SWIFT [ 34 ], and GLENMORE [ 35 ].…”

“…There are a number of computational models that can account for many of the behavioral phenomena associated with reading; however, most of those models have been developed to account for reading of alphabetic writing systems, such as E-Z Reader model[ 33 ], SWIFT [ 34 ], and GLENMORE [ 35 ]. Very few models have been extended to delineate the processes associated with sentence-level reading in non-alphabetic languages [ 32 ]. To date, the only exception is the model reported by Rayner, Li, and Pollatsek [ 36 ].…”